Machine learning-based optimisation in a two-echelon logistics network for the dry port operation in China-Reference-Cited by-同舟云学术

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Machine learning-based optimisation in a two-echelon logistics network for the dry port operation in China

Published:2023-09-06 Issue:1 Volume:10 Page:
ISSN:2330-2674
Container-title:International Journal of Systems Science: Operations & Logistics
language:en
Short-container-title:International Journal of Systems Science: Operations & Logistics

Author:

Li Qin¹,Wang Yu¹²,Xiong Yu³,Zhang Shu¹²,Zhou Yu¹²

Affiliation:

1. School of Economics and Business Administration, Chongqing University, Chongqing, People’s Republic of China

2. Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, People’s Republic of China

3. Surrey Business School, University of Surrey, Guildford, UK

Funder

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Information Systems and Management,Management Science and Operations Research,Information Systems,Management Information Systems

Link

https://www.tandfonline.com/doi/pdf/10.1080/23302674.2023.2252321

Reference84 articles.

1. DesPatNet25: Data encryption standard cipher model for accurate automated construction site monitoring with sound signals

2. Location, Allocation and Routing of Temporary Health Centers in Rural Areas in Crisis, Solved by Improved Harmony Search Algorithm

3. Multi-depot multi-compartment vehicle routing problem, solved by a hybrid adaptive large neighborhood search

4. An adaptive large neighborhood search for a vehicle routing problem with multiple routes

5. Analytics and machine learning in vehicle routing research

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